Meta title: Strava: Technical Guide for Power Users

Meta description: Explore Strava’s API, telemetry, and privacy for advanced users. Learn about GPX, OAuth, segments, and practical integration tips.

Strava for Power Users: A Technical Overview

Strava has become the de facto telemetry hub for athletes and developers, and understanding its data model is essential for any engineer integrating fitness data. This overview addresses how Strava stores and exposes activity data, how to interact with its API, and practical caveats around GPS, sensors, and privacy for technically minded users.

Data and telemetry

Strava collects GPS traces, elevation profiles, heart rate, cadence, and power when available, and stores them in a normalized activity model. Raw GPS sampling rates vary by device and influence smoothing and elevation correction. Exporting GPX or FIT files preserves the telemetry for offline analysis, while Activity Streams provide segmented arrays for distance, time, and altitude useful for reprocessing or resampling. When merging sensor data from ANT+ or Bluetooth devices, timestamp alignment becomes the single biggest source of error.

API and authentication

Strava’s REST API uses OAuth 2.0 for authorization and supports endpoints for activities, segments, and athlete profiles. Rate limits and scoped tokens require careful handling in long-running integrations; webhooks offer efficient event-driven updates instead of polling. When building a backend, refresh tokens must be securely stored and rotated, and payload verification should validate signature headers.

Segments, analysis, and privacy

Segments and KOM/QOM leaderboards enable comparative analytics but introduce privacy considerations. Heatmaps and explored routes can reveal habitual locations; adjusting privacy zones and activity visibility mitigates exposure. For reproducible analytics, export canonical files, record device metadata, and document any smoothing or correction steps applied by Strava.

Held og lykke Charlie.